Wafia Adouane Department of FLOV University of Gothenburg Box 100 SE-405 30, Gothenburg, Sweden wafia.adouane@gu.se Nasredine Semmar CEA Saclay – Nano-INNOV Institut CARNOT CEA LIST 91191 Gif-sur-Yvette Cedex, France nasredine.semmar@cea.fr Richard Johansson Department of Computer Science and Engineering University of Gothenburg

http://utbildning.gu.se/ViewPage.action?siteNodeId=597348&languageId=100000&contentId=-1&eventId=70137133944 Enligt regeringens Agenda 2030 ska all undervisning ta

Om avkoloniserande läsningars möjlighet. Svensson, Therese. Early Modern Swedish society. Nilsen, Andrine. Adouane, Wafia.

2018. “Improving Neural Network Performance by Injecting Background Knowledge: Detecting Code-switching and Borrowing in Algerian texts”. In Proceedings of the 3rd Workshop on Computational Approaches to Linguistic Code-Switching, pages 20–28. Wafia Adouane Department of FLOV University of Gothenburg Box 100 SE-405 30, Gothenburg, Sweden wafia.adouane@gu.se Nasredine Semmar CEA Saclay – Nano-INNOV Institut CARNOT CEA LIST 91191 Gif-sur-Yvette Cedex, France nasredine.semmar@cea.fr Richard Johansson Department of Computer Science and Engineering University of Gothenburg Semantic Scholar profile for Wafia Adouane, with 4 highly influential citations and 15 scientific research papers. Cordially welcome to the public defence of Wafia Adouane's doctoral thesis on Wednesday 2 September, at 17:00 online via Zoom. The title is Natural Language Processing for Low-resourced Code-switched Colloquial Languages – The Case of Algerian Language. Waﬁa Adouane, Jean-Philippe Bernardy and Simon Dobnik Department of Philosophy, Linguistics and Theory of Science (FLoV), Centre for Linguistic Theory and Studies in Probability (CLASP), University of Gothenburg {wafia.adouane,jean-philippe.bernardy,simon.dobnik}@gu.se Abstract We explore the extent to which neural net- WAFIA ADOUANE Department of Philosophy, Linguistics and Theory of Science isbn: 978-91-7833-958-7 (print) isbn: 978-91-7833-959-4 (pdf) Natural Language Processing for Low-resourced Code-Switched Colloquial Languages Wafia Adouane View the profiles of people named Wafia Adouane.

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Wafia Adouane's 9 research works with 48 citations and 395 reads, including: Neural Models for Detecting Binary Semantic Textual Similarity for Algerian and MSA

To our knowledge, no previous works were done for Gulf Arabic sentiment analysis despite the fact that it is present in different online platforms. Wafia Adouane, Nasredine Semmar, and Richard Johansson.

Wafia Adouane, Nasredine Semmar, and Richard Jo- hansson. 2016. ASIREM Participation at the Dis- criminating Similar Languages Shared Task 2016.

Moreover, we compiled sentiment Wafia Adouane, Richard Johansson (2016): Gulf Arabic Resource Building for Sentiment Analysis, i Proceedings of the Language Resources and Evaluation Conference (LREC), 23-28 May 2016, Portorož, Slovenia. wafia.gu@gmail.com, richard.johansson@gu.se Abstract This paper deals with building linguistic resources for Gulf Arabic, one of the Arabic variations, for sentiment analysis task using Wafia Adouane, 35 Studiegången 8 lgh 1003 Göteborg. Kvinna; Gift; Lokesh Menta, 31 Studiegången 8 lgh 1004 Göteborg. Man; Ej gift; Linus Jonathan Van Der Putten Expand Doctoral student at the University of Gothenburg Minimize Doctoral student at the University of Gothenburg http://utbildning.gu.se/ViewPage.action?siteNodeId=597348&languageId=100000&contentId=-1&eventId=70137133944 Enligt regeringens Agenda 2030 ska all undervisning ta We explore the extent to which neural networks can learn to identify semantically equivalent sentences from a small variable dataset using an end-to-end training. We collect a new noisy non-standardised user-generated Algerian (ALG) dataset and also translate it to Modern Standard Arabic (MSA) which serves as its regularised counterpart. We compare the performance of various models on both http://ips.gu.se/ViewPage.action?siteNodeId=529817&calendarIds=1764699888&fromSiteNodeId=499500&startDateTime=2012-10-28&endDateTime=2012-10-28 The top 25 events https://webresources.gu.se/ViewPage.action?siteNodeId=597348&languageId=100000&contentId=-1&eventId=70137133944 Enligt regeringens Agenda 2030 ska all undervisning ta https://webresources.gu.se/RSS_Services/Calendar_dynamic_RSS?categoryNames=&calendarIds=&fromSiteNodeId=529651&startDateTime=2019-08-03&endDateTime=2019-08-10 The top http://hum.gu.se/ViewPage.action?siteNodeId=529817&languageId=100000&contentId=-1&fromSiteNodeId=535137&startDateTime=2013-09-24&endDateTime=2013-09-24&calendarMonth http://kultur.gu.se/ViewPage.action?siteNodeId=529817&languageId=100000&contentId=-1&categoryNames=dissertation&calendarIds=163&fromSiteNodeId=529651&startDateTime http://bioenv.gu.se/ViewPage.action?siteNodeId=529817&languageId=100001&contentId=-1&fromSiteNodeId=499482&siteNodeId=499482&languageId=100001&contentId=-1 The top 25 http://hum.gu.se/ViewPage.action?siteNodeId=529817&languageId=100000&contentId=-1&fromSiteNodeId=535137&startDateTime=2013-06-13&endDateTime=2013-06-13&print=true http://hum.gu.se/ViewPage.action?siteNodeId=529817&languageId=100000&contentId=-1&fromSiteNodeId=535137&startDateTime=2011-03-03&endDateTime=2011-03-03 LINGUISTICS AND THEORY OF SCIENCE. AUTOMATIC DETECTION OF UNDER-.

E-mail: susanna.myyry@gu.se. Quick Links. News. Recruitment. CLASP GU page.
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Wafia Adouane PhD in Computational Linguistics Göteborg, Sverige 5 kontakter. Gå med för att skapa kontakt University of Gothenburg. Anmäl profilen Info I am a lucky person who does exactly what she is passionate about, i.e., I take it as having fun rather than working. It was obvious for me to specialise Wafia Adouane: Natural Language Processing for Low-resourced Code-switched Colloquial Languages - The Case of Algerian Language Research.

Abstract This paper seeks to examine the effect of including background knowledge in the form of character pre-trained neural language model (LM), and data bootstrapping to overcome the problem of unbalanced limited resources.
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About Wafia Adouane. I am a PhD student in Computational Linguistics studying how to make computers understand texts where several languages or language varieties are used simultaneously and what problems are encountered by computational linguists while processing unstandardized languages for which very little written resources exist.

Office Hours: Monday-Friday (9.00am - 5.00pm) Phone: Phone +46 31-786 0000. E-mail: susanna.myyry@gu.se. Quick Links.

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Early Modern Swedish society. Nilsen, Andrine. Adouane, Wafia. Vithetens koagulerade hjärta. Om avkoloniserande läsningars möjlighet. Svensson, Therese.

AUTOMATIC DETECTION OF UNDER-. RESOURCED LANGUAGES.

We explore the extent to which neural networks can learn to identify semantically equivalent sentences from a small variable dataset using an end-to-end training. We collect a new noisy non-standardised user-generated Algerian (ALG) dataset and also translate it to Modern Standard Arabic (MSA) which serves as its regularised counterpart. We compare the performance of various models on both

Dörr 3 från vänster. Wafia Adouane, 35 årFlyttade hit för 1 år sedan.

Association for Computational Linguistics. VIEW ARTICLE Wafia Adouane, Simon Dobnik, Jean-Philippe Bernardy, and Nasredine Semmar. 2018. Wafia Adouane was a PhD Student at CLASP. Yuri Bizzoni. PhD student.